基于建筑物提取的精细尺度人口估算研究  

Investigation on Small-area Population Estimation Based on Building Extraction

作　　者：冯甜甜[1] 龚健雅[1] 

机构地区：[1]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079

出　　处：《遥感技术与应用》2010年第3期323-327,共5页Remote Sensing Technology and Application

基　　金：国家自然科学基金创新研究群体资助项目(40721001);国家973计划资助项目(2006CB701304)资助

摘　　要：以精细尺度的人口估算为目标,提出一种根据居民区建筑物属性估算人口数量的方法。首先基于Dempster-Shafer证据理论,结合LiDAR数据和高分辨率遥感影像进行建筑物的自动提取。根据土地利用分类图排除提取结果中的非居民区建筑后,按照线性回归的思想,通过对居民建筑物的数量、面积、体积等几何属性的优化选择建立人口估算模型。实验表明,利用该估算模型能够获得较高精度的小面积目标区域上的估算结果。该方法提高了人口估算的精细程度和自动化程度。In order to estimate the population of small area,a new population estimation method based on residential building attributes is presented.Firstly,buildings are extracted combining LiDAR data with high-resolution remote sensing images,using Dempster-Shafer theory of evidence.Then,all the non-residential buildings are excluded from extraction results according to land use classification map,and the population estimation model is generated by optimization choice of geometric attributes of residential buildings,such as building counts,building areas,and building volumes,based on linear regression method.The results demonstrated that proposed model yielded good small-area population estimation results,and the proposed method improved the precision and automatic of population estimation.

关 键 词：建筑物提取 人口估算 小面积区域 DEMPSTER-SHAFER理论 线性回归分析 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]